Towards precision oncology in RET-aberrant cancers.
Ontology highlight
ABSTRACT:
SUBMITTER: Subbiah V
PROVIDER: S-EPMC5444346 | biostudies-literature |
REPOSITORIES: biostudies-literature
Similar Datasets
Project description:Rearranged during transfection (RET) is a protooncogene that encodes for receptor tyrosine kinase with downstream effects on multiple cellular pathways. Activating RET alterations can occur and lead to uncontrolled cellular proliferation as a hallmark of cancer development. Oncogenic RET fusions are present in nearly 2% of patients with non-small cell lung cancer (NSCLC), 10-20% of patients with thyroid cancer, and <1% across the pan-cancer spectrum. In addition, RET mutations are drivers in 60% of sporadic medullary thyroid cancers and 99% of hereditary thyroid cancers. The discovery, rapid clinical translation, and trials leading to FDA approvals of selective RET inhibitors, selpercatinib and pralsetinib, have revolutionized the field of RET precision therapy. In this article, we review the current status on the use of the selective RET inhibitor, selpercatinib, in RET fusion-positive tumors: NSCLC, thyroid cancers, and the more recent tissue-agnostic activity leading to FDA approval.
| S-EPMC10288430 | biostudies-literature
Project description:Rearranged during transfection (RET) is involved in the physiological development of some organ systems. Activating RET alterations via either gene fusions or point mutations are potent oncogenic drivers in non-small cell lung cancer, thyroid cancer, and in multiple diverse cancers. RET-altered cancers were initially treated with multikinase inhibitors (MKIs). The efficacy of MKIs was modest at the expense of notable toxicities from their off-target activity. Recently, highly potent and RET-specific inhibitors selpercatinib and pralsetinib were successfully translated to the clinic and FDA approved. We summarize the current state-of-the-art therapeutics with preclinical and clinical insights of these novel RET inhibitors, acquired resistance mechanisms, and future outlooks.
| S-EPMC8599646 | biostudies-literature
Project description:Aberrant activation of the RET proto-oncogene is implicated in a plethora of cancers. RET gain-of-function point mutations are driver events in multiple endocrine neoplasia 2 (MEN2) syndrome and in sporadic medullary thyroid cancer, while RET rearrangements are driver events in several non-medullary thyroid cancers. Drugs able to inhibit RET have been used to treat RET-mutated cancers. Multikinase inhibitors were initially used, though they showed modest efficacy and significant toxicity. However, new RET selective inhibitors, such as selpercatinib and pralsetinib, have recently been tested and have shown good efficacy and tolerability, even if no direct comparison is yet available between multikinase and selective inhibitors. The advent of high-throughput technology has identified cancers with rare RET alterations beyond point mutations and fusions, including RET deletions, raising questions about whether these alterations have a functional effect and can be targeted by RET inhibitors. In this mini review, we focus on tumors with RET deletions, including deletions/insertions (indels), and their response to RET inhibitors.
| S-EPMC9449844 | biostudies-literature
Project description:Precision oncology and its diagnostic tools are essential for developing personalized cancer treatments. The purpose of this study was to integrate data on the digital patterns of reticulin fiber scaffolding and the immune cell infiltrate, transcriptomic and epigenetic profiles in aggressive uterine adenocarcinoma (uADC), uterine leiomyosarcoma (uLMS) and their respective lung metastases (LM-uADC and LM-uLMS), with the aim of obtaining key tumor microenvironment (TME) biomarkers that can help improve metastatic prediction and shed light on potential therapeutic targets.
2022-12-16 | GSE216313 | GEO
Project description:The incidence of new cancer cases is expected to increase significantly in the future, posing a worldwide problem. In this regard, precision oncology and its diagnostic tools are essential for developing personalized cancer treatments. Nowadays, it is almost impossible to separate technology and digitization from medicine and health sciences, and digital pathology (DP) is emerging as one of the most influential technologies in the transition towards the 4P of new medicine (preventive, participatory, personalized and predictive). DP is a particularly key strategy to study the interactions of tumor cells and the tumor microenvironment (TME), which play a crucial role in tumor initiation, progression and metastasis. The purpose of this study was to integrate data on the digital patterns of reticulin fiber scaffolding and the immune cell infiltrate, transcriptomic and epigenetic profiles in aggressive uterine adenocarcinoma (uADC), uterine leiomyosarcoma (uLMS) and their respective lung metastases, with the aim of obtaining key TME biomarkers that can help improve metastatic prediction and shed light on potential therapeutic targets. Automatized algorithms were used to analyze reticulin fiber architecture and immune infiltration in colocalized regions of interest (ROIs) of 133 invasive tumor front (ITF), 89 tumor niches and 70 target tissues in a total of six paired samples of uADC and nine of uLMS. Microdissected tissue from the ITF was employed for transcriptomic and epigenetic studies in primary and metastatic tumors. Reticulin fiber scaffolding was characterized by a large and loose reticular fiber network in uADC, while dense bundles were found in uLMS. Notably, more similarities between reticulin fibers were observed in paired uLMS then paired uADCs. Transcriptomic and multiplex immunofluorescence-based immune profiling showed a higher abundance of T and B cells in primary tumor and in metastatic uADC than uLMS. Moreover, the epigenetic signature of paired samples in uADCs showed more differences than paired samples in uLMS. Some epigenetic variation was also found between the ITF of metastatic uADC and uLMS. Altogether, our data suggest a correlation between morphological and molecular changes at the ITF and the degree of aggressiveness. The use of DP tools for characterizing reticulin scaffolding and immune cell infiltration at the ITF in paired samples together with information provided by omics analyses in a large cohort will hopefully help validate novel biomarkers of tumor aggressiveness, develop new drugs and improve patient quality of life in a much more efficient way.
2022-10-06 | GSE214779 | GEO
Project description:Esophageal (OC), gastric (GC) and colorectal (CRC) cancers are amongst the digestive track tumors with higher incidence and mortality due to significant molecular heterogeneity. This constitutes a major challenge for patients' management at different levels, including non-invasive detection of the disease, prognostication, therapy selection, patient's follow-up and the introduction of improved and safer therapeutics. Nevertheless, important milestones have been accomplished pursuing the goal of molecular-based precision oncology. Over the past five years, high-throughput technologies have been used to interrogate tumors of distinct clinicopathological natures, generating large-scale biological datasets (e.g. genomics, transcriptomics, and proteomics). As a result, GC and CRC molecular subtypes have been established to assist patient stratification in the clinical settings. However, such molecular panels still require refinement and are yet to provide targetable biomarkers. In parallel, outstanding advances have been made regarding targeted therapeutics and immunotherapy, paving the way for improved patient care; nevertheless, important milestones towards treatment personalization and reduced off-target effects are also to be accomplished. Exploiting the cancer glycoproteome for unique molecular fingerprints generated by dramatic alterations in protein glycosylation may provide the necessary molecular rationale towards this end. Therefore, this review presents functional and clinical evidences supporting a reinvestigation of classical serological glycan biomarkers such as sialyl-Tn (STn) and sialyl-Lewis A (SLeA) antigens from a tumor glycoproteomics perspective. We anticipate that these glycobiomarkers that have so far been employed in non-invasive cancer prognostication may hold unexplored value for patients' management in precision oncology settings.
| S-EPMC7163443 | biostudies-literature
Project description:Precision oncology informed by genomic information has evolved in leaps and bounds over the last decade. Although non-small cell lung cancer (NSCLC) has moved to center-stage as the poster child of precision oncology, multiple targetable genomic alterations have been identified in various cancer types. RET alterations occur in roughly 2% of all human cancers. The role of RET as oncogenic driver was initially identified in 1985 after the discovery that transfection with human lymphoma DNA transforms NIH-3T3 fibroblasts. Germline RET mutations are causative of multiple endocrine neoplasia type 2 syndrome, and RET fusions are found in 10-20% of papillary thyroid cases and are detected in most patients with advanced sporadic medullary thyroid cancer. RET fusions are oncogenic drivers in 2% of Non-small cell lung cancer. Rapid translation and regulatory approval of selective RET inhibitors, selpercatinib and pralsetinib, have opened up the field of RET precision oncology. This review provides an update on RET precision oncology from bench to bedside and back. We explore the impact of selective RET inhibitor in patients with advanced NSCLC, thyroid cancer, and other cancers in a tissue-agnostic fashion, resistance mechanisms, and future directions.
| S-EPMC10141525 | biostudies-literature
Project description:Poly-ADP ribose polymerase (PARP) inhibitors are currently used in the treatment of several cancers carrying mutations in the breast and ovarian cancer susceptibility genes BRCA1 and BRCA2, with many more potential applications under study and in clinical trials. Here, we discuss the potential for extending PARP inhibitor therapies to tumours with deficiencies in the DNA damage-activated protein kinase, Ataxia-Telangiectasia Mutated (ATM). We highlight our recent findings that PARP inhibition alone is cytostatic but not cytotoxic in ATM-deficient cancer cells and that the combination of a PARP inhibitor with an ATR (ATM, Rad3-related) inhibitor is required to induce cell death.
| S-EPMC7140103 | biostudies-literature
Project description:The recent accumulation of cancer genomic data provides an opportunity to understand how a tumor's genomic characteristics can affect its responses to drugs. This field, called pharmacogenomics, is a key area in the development of precision oncology. Deep learning (DL) methodology has emerged as a powerful technique to characterize and learn from rapidly accumulating pharmacogenomics data. We introduce the fundamentals and typical model architectures of DL. We review the use of DL in classification of cancers and cancer subtypes (diagnosis and treatment stratification of patients), prediction of drug response and drug synergy for individual tumors (treatment prioritization for a patient), drug repositioning and discovery and the study of mechanism/mode of action of treatments. For each topic, we summarize current genomics and pharmacogenomics data resources such as pan-cancer genomics data for cancer cell lines (CCLs) and tumors, and systematic pharmacologic screens of CCLs. By revisiting the published literature, including our in-house analyses, we demonstrate the unprecedented capability of DL enabled by rapid accumulation of data resources to decipher complex drug response patterns, thus potentially improving cancer medicine. Overall, this review provides an in-depth summary of state-of-the-art DL methods and up-to-date pharmacogenomics resources and future opportunities and challenges to realize the goal of precision oncology.
| S-EPMC7711267 | biostudies-literature
Project description:The advent of next-generation sequencing (NGS) has provided unprecedented insight into the molecular complexity of pancreatic ductal adenocarcinoma (PDAC). This has led to the emergence of biomarker-driven treatment paradigms that challenge empiric treatment approaches. However, the growth of sequencing technologies is outpacing the development of the infrastructure required to implement precision oncology as routine clinical practice. Addressing these logistical barriers is imperative to maximize the clinical impact of molecular profiling initiatives. In this review, we examine the evolution of precision oncology in PDAC, spanning from germline testing for cancer susceptibility genes to multi-omic tumor profiling. Furthermore, we highlight real-world challenges to delivering precision oncology for PDAC, and propose strategies to improve the generation, interpretation, and clinical translation of molecular profiling data.
| S-EPMC7563487 | biostudies-literature